I’m a PhD student advised by Prof. Chaoyue Liu, researching aspects of optimization theory, intrinsic interpretability, & domain generalization within deep learning.

I like to approach research through rigorous mathematical foundations. Recently, I’ve been developing approaches that encode intuitive biases within the architecture and optimization of deep learning models by leveraging provably faithful interpretability.

Besides deep learning, I enjoy hiking, motor racing, chess, swimming, mountain biking (unfortunately I suck at this one) & really anything that gets my adrenaline pumping.

If your research is along similar lines I’d love to learn about the approaches you’re taking and exchange perspective. Please feel free to reach out – I’m accessible through email and matrix!